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Learner Reviews & Feedback for Applied Social Network Analysis in Python by University of Michigan

4.6
stars
2,681 ratings

About the Course

This course will introduce the learner to network analysis through tutorials using the NetworkX library. The course begins with an understanding of what network analysis is and motivations for why we might model phenomena as networks. The second week introduces the concept of connectivity and network robustness. The third week will explore ways of measuring the importance or centrality of a node in a network. The final week will explore the evolution of networks over time and cover models of network generation and the link prediction problem. This course should be taken after: Introduction to Data Science in Python, Applied Plotting, Charting & Data Representation in Python, and Applied Machine Learning in Python....

Top reviews

NK

May 2, 2019

This course is a excellent introduction to social network analysis. Learnt a lot about how social network works. Anyone learning Machine Learning and AI should definitely take this course. It's good.

JL

Sep 23, 2018

It was an easy introductory course that is well structured and well explained. Took me roughly a weekend and I thoroughly enjoyed it. Hope the professor follows up with more advanced material.

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351 - 375 of 452 Reviews for Applied Social Network Analysis in Python

By Ishrath I

•

Mar 6, 2023

The professor was great! The way he explained everything was clear and understandable. The mentor, Uwe, in the course was also super helpful when other students or I needed assistance during assignments. The only reason why I gave this course 4 stars rather than a 5 was that there were many errors in the assignments and auto grader.

By Dipjyoti D

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Dec 1, 2022

Good introductory course for conceptual understanding of Network Analysis in Python. Good assignments, would be great to have more real world examples and hands-on business case studies for application of Network Analysis in different Industries. Also, they should update the course to use recent version of Networkx - 2.8 library.

By Vani K - P

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Jun 12, 2020

Its a amazing course for beginners with little Python experience. The lectures and quiz are simple and assignments are really challenging. If you are looking for Social Networks course which covers nook and corners of Social Networks Analysis then this course is not for you.

By Brandan S

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Sep 19, 2017

Pro: Required interpretation of methods presented for application on assignments without explicit direction. Required application of knowledge gained in previous specialization courses.

Con: Explanations of social network analyses were limited in number and shallow in coverage.

By Robert J K

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Dec 18, 2018

The course starts off a bit slow but gets you used to the NetworkX module. The last exercise is a pretty neat culmination of the this course and specialization. It would have been cool for it to also involve text mining, but I enjoyed it and the course in general.

By Carlos F P

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Feb 7, 2020

The course provides a great introduction to graph analytics, I consider that the social network applications are very sparse or missing in action altogether. Nonetheless, overall great content and practice of extracting information from networks with Python.

By Isaac H

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Apr 11, 2023

Did not make clear the prerequisite requirement to understand machine learning classifiers using sklearn library. Had to go back and teach this to myself in a week in order to complete finial assignment. This should be in the prerequisites for the class.

By Jose P

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Dec 8, 2018

Social Network was completely new to me and I found this course provided basic and more detailed information about the matter, and also enough documentation to continue learning. I see there is much more to learn, but the course was a great introduction.

By Thomas L

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Jan 26, 2021

Course was very straightforward application of the lecture materials. Not as challenging as the first three courses of this specialization, but nevertheless it was instructed very clearly and was informative. Would recommend this course.

By Srinivas R

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Oct 9, 2017

Good overview of network concepts using networkx - wish the course were a few weeks longer for it finishes just when you feel you can begin to something useful with the basics you have learned - but you do learn the basics.

By bob n

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Sep 22, 2020

Good basic course, well paced. I liked the instructor. Weekly assignments fair, some tougher than others. Occasionally finicky Auto grader a bit like artillery, need to send a couple of rounds over to home in on target.

By Devansh K

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Dec 28, 2020

Extremely detailed and challenging course. The assignments require a lot of thinking and skill. Gives a comprehensive overview of social network analysis and a good way for any novice python coder to improve their skills

By Bernardo A

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Oct 8, 2017

Really good overview of concepts and analysis related to 'graphs'. Could be more challenging when it comes to projects: for example, teach students to gather real data from twitter or facebook and make graphs with it.

By Chris M

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Oct 7, 2017

I know its hard to go in deep detail with these courses. If you used one graph and gradually built upon it through the course it may reinforce the concepts better. Thoroughly enjoyed though, learned a lot.

By Chad A

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Jan 13, 2018

The material and assignments were great and well aligned. The autograder for the Jupyter Notebooks was finicky at best and resulted in lots of time wasted getting formatting correct.

By Tess P

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Nov 16, 2022

I really like the content of the course.

What needs to improve is the networkx package is used in the lab. It's an old version with old functions and they are not working sometime.

By Vivien A

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Mar 16, 2021

Great content but assignment / auto grader sometimes difficult to deal with. In particular, errors not clearly described. Much time wasted due to wrong package version, etc. etc.

By Eric M

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Oct 9, 2017

This was an excellent overview of using and analyzing graphs with Python. I learned a lot, got to apply my learning from previous courses, and I earned my Specialization!

By Raul M

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Jul 6, 2018

Great class for an introduction to networks.I didn't give it 5 stars because it didn't give me enough information to apply the concepts learned to real life projects.

By Vishal S

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Jul 16, 2018

Lectures are very well-designed. Especially, the assignment of week 4 is too good, that give me an overview of how we can apply machine learning in network analysis.

By Steffen H

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Nov 20, 2018

Course was ok, the assignments are not too difficult. I wish the course would provided more insights and discussions of the presented metrics of centrality though.

By Edvard M

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Aug 1, 2022

Would have appreciated more theoretic approach even for applied science course, but did like the content & much appreciate staff on being so helpful in forums

By Sean D

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Jun 26, 2019

Overall, good course. It could use more explicit examples of NetworkX in the actual Jupyter Notebook itself, but the coverage of the material is high quality.

By Ezequiel P

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Sep 16, 2020

Great course! The topic is very interesting! I would have liked it to have more hands-on approach during the lectures, but the course quality is great

By YUJI H

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Jun 28, 2018

The presentation documents are very helpful to understand the lectures. If they can be downloaded to our local laptop, I evaluate this course 5 stars.